# Natural Language Toolkit: Some texts for exploration in chapter 1 of the book # # Copyright (C) 2001-2017 NLTK Project # Author: Steven Bird # # URL: # For license information, see LICENSE.TXT from __future__ import print_function from nltk.corpus import (gutenberg, genesis, inaugural, nps_chat, webtext, treebank, wordnet) from nltk.text import Text from nltk.probability import FreqDist print("*** Introductory Examples for the NLTK Book ***") print("Loading text1, ..., text9 and sent1, ..., sent9") print("Type the name of the text or sentence to view it.") print("Type: 'texts()' or 'sents()' to list the materials.") text1 = Text(gutenberg.words('melville-moby_dick.txt')) print("text1:", text1.name) text2 = Text(gutenberg.words('austen-sense.txt')) print("text2:", text2.name) text3 = Text(genesis.words('english-kjv.txt'), name="The Book of Genesis") print("text3:", text3.name) text4 = Text(inaugural.words(), name="Inaugural Address Corpus") print("text4:", text4.name) text5 = Text(nps_chat.words(), name="Chat Corpus") print("text5:", text5.name) text6 = Text(webtext.words('grail.txt'), name="Monty Python and the Holy Grail") print("text6:", text6.name) text7 = Text(treebank.words(), name="Wall Street Journal") print("text7:", text7.name) text8 = Text(webtext.words('singles.txt'), name="Personals Corpus") print("text8:", text8.name) text9 = Text(gutenberg.words('chesterton-thursday.txt')) print("text9:", text9.name) def texts(): print("text1:", text1.name) print("text2:", text2.name) print("text3:", text3.name) print("text4:", text4.name) print("text5:", text5.name) print("text6:", text6.name) print("text7:", text7.name) print("text8:", text8.name) print("text9:", text9.name) sent1 = ["Call", "me", "Ishmael", "."] sent2 = ["The", "family", "of", "Dashwood", "had", "long", "been", "settled", "in", "Sussex", "."] sent3 = ["In", "the", "beginning", "God", "created", "the", "heaven", "and", "the", "earth", "."] sent4 = ["Fellow", "-", "Citizens", "of", "the", "Senate", "and", "of", "the", "House", "of", "Representatives", ":"] sent5 = ["I", "have", "a", "problem", "with", "people", "PMing", "me", "to", "lol", "JOIN"] sent6 = ['SCENE', '1', ':', '[', 'wind', ']', '[', 'clop', 'clop', 'clop', ']', 'KING', 'ARTHUR', ':', 'Whoa', 'there', '!'] sent7 = ["Pierre", "Vinken", ",", "61", "years", "old", ",", "will", "join", "the", "board", "as", "a", "nonexecutive", "director", "Nov.", "29", "."] sent8 = ['25', 'SEXY', 'MALE', ',', 'seeks', 'attrac', 'older', 'single', 'lady', ',', 'for', 'discreet', 'encounters', '.'] sent9 = ["THE", "suburb", "of", "Saffron", "Park", "lay", "on", "the", "sunset", "side", "of", "London", ",", "as", "red", "and", "ragged", "as", "a", "cloud", "of", "sunset", "."] def sents(): print("sent1:", " ".join(sent1)) print("sent2:", " ".join(sent2)) print("sent3:", " ".join(sent3)) print("sent4:", " ".join(sent4)) print("sent5:", " ".join(sent5)) print("sent6:", " ".join(sent6)) print("sent7:", " ".join(sent7)) print("sent8:", " ".join(sent8)) print("sent9:", " ".join(sent9))